ABSTRACT
Introduction: CARTITUDE-2 (NCT04133636) is a phase 2, multicohort study evaluating cilta-cel, an anti-BCMA CAR-T therapy, in several multiple myeloma (MM) patient (pt) populations. Objective(s): To report updated results with longer follow-up on cohort C pts with previous exposure to a non-cellular anti- BCMA immunotherapy. Method(s): Cohort C pts had progressive MM after treatment (tx) with a proteasome inhibitor, immunomodulatory drug, anti-CD38 antibody, and non-cellular BCMA-targeting agent. A single cilta-cel infusion (target dose 0.75x106 CAR+ viable T cells/kg) was administered 5-7 days post lymphodepletion. Primary endpoint was minimal residual disease (MRD) negativity at 10-5. Secondary endpoints included overall response rate (ORR), duration of response (DOR), and adverse events (AEs). Result(s): As of June 1, 2022, 20 pts (13 ADC exposed;7 BsAb exposed) were treated with cilta-cel;4 pts did not receive cilta-cel due to either low cellular yield (n=2, 1 in each group) or death due to progressive disease (PD) prior to dosing (n=2, 1 in each group) and 6 pts received anti-BCMA tx as their last line of therapy (n=4 ADC, n=2 BsAb). During prior anti-BCMA tx, best responses included VGPR (ADC: 2 pts;BsAb: 1 pt), sCR (ADC: 1 pt), and CR (BsAb: 1 pt);the rest had best response of stable disease or PD (1 pt not evaluable). Baseline characteristics are presented in Figure 1A. Median time from last anti- BCMA agent to cilta-cel infusion was 195 d;median administered dose of cilta-cel was 0.65x106 CAR+ viable T cells/kg. At a median follow-up of 18.0 mo, 7/10 evaluable pts (70%) were MRD negative at 10-5 (ADC: 5/7 [71.4%], BsAb: 2/3 [66.7%]). ORR: full cohort, 60%;ADC, 61.5%;BsAb, 57.1% (Figure 1B). Median DOR: full cohort, 12.8 mo;ADC, 12.8 mo;BsAb, 8.2 mo. Median PFS: full cohort, 9.1 mo;ADC, 9.5 mo;BsAb, 5.3 mo. Cilta-cel responders had a shorter median duration of last anti- BCMA agent exposure (29.5 d) compared with non-responders (63.5 d). Responders also had a longer median time from last anti-BCMA tx exposure to apheresis (161.0 d) than non-responders (56.5 d). Most common AEs were hematologic. CRS: n=12 (60%;all Gr1/2), median time to onset 7.5 d, median duration 6.0 d. ICANS: n=4 (20%, 2 Gr3/4), median time to onset 9.0 d, median duration 7.0 d. No patient had movement or neurocognitive tx emergent AE/parkinsonism. There were 12 deaths (PD: 8;COVID-19 pneumonia: 2 [not tx related];subarachnoid hemorrhage: 1 [not tx related];C. difficile colitis: 1 [tx related]). (Figure Presented)(Figure Presented)Conclusions: Pts with heavily pretreated MM and previous exposure to a non-cellular anti-BCMA therapy had favorable responses to cilta-cel. However, depth and DOR appear lower than that seen in anti-BCMA-naive pts treated with cilta-cel (at 27.7 mo, median DOR was not reached in heavily pre-treated but anti-BCMA naive CARTITUDE-1 pts). These data may inform tx plans, including sequencing and washout period between BCMA-targeting agentsCopyright © 2023 American Society for Transplantation and Cellular Therapy
ABSTRACT
Background: A lot of attention has been drawn to the identification of predictors of VTE in COVID-19 patients, and an accurate clinical prediction model is still lacking in this context. Aims: To develop a clinical prediction model using artificial intelligence techniques, to predict VTE in COVID-19 patients, using variables easily available upon hospital admission. Methods: This multicenter cohort included consecutive adult patients (≥ 18 years-old) with laboratory-confirmed COVID-19 from 37 Brazilian hospitals from 17 cities, between March and September 2020. Study data were collected from medical records using Research Electronic Data Capture (REDCap) tools. We trained multiple machine learning models on various combinations of structured and non-structured features, calibrated to reflect a probability distribution while predicting the desired clinical outcome. Subsequently, we analyzed the relationship between this model ' s predicted confidence score and the fraction of false negatives in the test sample to devise a splitting point where no false negatives would occur, thus calibrating for sensitivity over specificity. The study was approved by the National Research Ethics Commission waiving off the application of informed consent. Results: The dataset included 6421 patients (median age 61 [P25-75 48-73] years-old, 54.8% men), 4.5% of them developed venous thromboembolic disease. Patient ' s age, sex and comorbidities, as well as their list of household prescription drugs, history of recent surgery and laboratory tests were significant predictors. Given a proper confidence level, our model predicted 100% of the true positive cases while eliminating a significant portion of the true negatives (Figure 1). (Figure Presented) Conclusions: This study suggests that an ensemble of decision rules can effectively predict COVID patients with high risk of VTE. It might be possible to decrease the use of anticoagulants while still treating patients with an appreciable likelihood of thromboembolism.
ABSTRACT
Background: Knowledge on the immunopathobiology of COVID-19 is rapidly increasing but most studies analyzed relatively small series of patients and immune features predictive of fatal outcome are unavailable for routine stratification. Furthermore, an increased risk of death in patients with hematological cancer infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified, but it remains unknown if this is related to possible immunosuppression caused by cancer itself and cytotoxic treatment. Aims: Characterize the immune response to SARS-CoV-2 in a large cohort of patients to identify high-risk immune biomarkers and evaluate the association between COVID-19 severity and immunosuppression in patients with hematological cancer. Methods: Multidimensional flow cytometry was used to conduct holistic and unbiased analyses of17 immune cell types on 780 peripheral blood samples obtained from 513 COVID-19 patients, 24 cases with non-SARS-CoV-2 infection and 36 age-matched healthy adults.167 COVID-19 patients had 207 longitudinal samples collected over time. RNA sequencing on FACSorted cells and high-resolution flow cytometry were used to perform a deeper characterization of various myeloid and lymphoid subsets in14 COVID-19 patients and4 healthy adults. Results: Immune profiles of COVID-19 patients were generally similar to those of age-matched patients with non-SARS-CoV-2 infection, but significantly different from those of age-matched healthy adults. When compared to the later, COVID-19 patients showed increased percentages of neutrophils, CD4+CD56+ T-cells, and plasmablasts, whereas levels of basophils, eosinophils, and non-classical monocytes, as well as double-negative, CD8loCD56-, CD8-/loCD56+ and CD8hiCD56- T-cells, and B-cells were decreased. Both transcriptional and immunophenotypic data in myeloid and lymphoid subsets suggested an association between COVID-19 severity and neutrophil activation, as well as significantly reduced levels of specific adaptive immune cell types. Unsupervised clustering analysis of 513 patients revealed three immunotypes in response to SARS-CoV-2 infection. One of them, present in14% of patients (n=74), was characterized by significantly lower percentages of all immune cell types except neutrophils and plasmablasts, and was significantly associated with more severe disease. Of note, 50% of COVID-19 patients with blood cancer displayed this immunotype. Accordingly, hematological patients showed a significantly higher frequency of admission into intensive care units (50% vs 5%, P<.001) and death (30% vs4%, P<.001) than patients without tumor did. On multivariate analysis incorporating age and comorbidities, the frequency of B-cells and non-classical monocytes were independent prognostic factors for overall survival. Indeed, <1% B-cells in peripheral blood was most strongly associated with risk of death. Among patients with immune monitoring during follow-up, significant changes in the relative distribution of eight immune cell types, including basophils, CD8loCD56- T-cells, and B-cells, were observed from the first to last peripheral blood sample between patients who survived or died. Summary/Conclusion: Our results accelerate our understanding of the immunopathobiology of COVID-19 and unveil an association between altered immune profiles in patients with hematological cancer and their poorer outcome. Reduced percentages of B-cells and non-classical monocytes are high-risk immune biomarkers that could be readily implemented in routine practice for risk-stratification of COVID-19.